*The author of this computation has been verified*

R Software Module: /rwasp_decomposeloess.wasp (opens new window with default values)

Title produced by software: Decomposition by Loess

Date of computation: Thu, 09 Dec 2010 20:38:28 +0000

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2010/Dec/09/t1291926992qpwq3icowgul4bo.htm/, Retrieved Thu, 09 Dec 2010 21:36:37 +0100

BibTeX entries for LaTeX users:

@Manual{KEY, author = {{YOUR NAME}}, publisher = {Office for Research Development and Education}, title = {Statistical Computations at FreeStatistics.org, URL http://www.freestatistics.org/blog/date/2010/Dec/09/t1291926992qpwq3icowgul4bo.htm/}, year = {2010}, } @Manual{R, title = {R: A Language and Environment for Statistical Computing}, author = {{R Development Core Team}}, organization = {R Foundation for Statistical Computing}, address = {Vienna, Austria}, year = {2010}, note = {{ISBN} 3-900051-07-0}, url = {http://www.R-project.org}, }

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

Dataseries X:

» Textbox « » Textfile « » CSV «

-820,8 993,3 741,7 603,6 -145,8 -35,1 395,1 523,1 462,3 183,4 791,5 344,8 -217,0 406,7 228,6 -580,1 -1550,4 -1447,5 -40,1 -1033,5 -925,6 -347,8 -447,7 -102,6 -2062,2 -929,7 -720,7 -1541,8 -1432,3 -1216,2 -212,8 -378,2 76,9 -101,3 220,4 495,6 -1035,2 61,8 -734,8 -6,9 -1061,1 -854,6 -186,5 244,0 -992,6 -335,2 316,8 477,6 -572,1 1115,2

Output produced by software:

Summary of computational transaction Raw Input view raw input (R code) Raw Output view raw output of R engine Computing time 2 seconds R Server 'George Udny Yule' @ 72.249.76.132 Seasonal Decomposition by Loess - Parameters Component Window Degree Jump Seasonal 501 0 51 Trend 19 1 2 Low-pass 13 1 2 Seasonal Decomposition by Loess - Time Series Components t Observed Fitted Seasonal Trend Remainder 1 -820.8 -1379.03721817852 -778.041359521869 515.478577700385 -558.237218178516 2 993.3 995.706139427682 501.216043944357 489.677816627961 2.40613942768169 3 741.7 892.181774367612 127.341170076851 463.877055555537 150.481774367612 4 603.6 887.2256684983 -115.428436604596 435.402768106295 283.625668498301 5 -145.8 65.7688876828117 -764.297368339865 406.928480657053 211.568887682812 6 -35.1 155.779054149494 -603.450748169431 377.471694019937 190.879054149494 7 395.1 166.563940875488 275.621151741692 348.014907382820 -228.536059124513 8 523.1 605.565387553075 126.498567905612 314.136044541314 82.4653875530746 9 462.3 700.491070647642 -56.148252347449 280.257181699807 238.191070647642 10 183.4 8.33500134328045 146.059762237946 212.405236418774 -175.064998656720 11 791.5 914.229158145035 524.217550717224 144.553291137741 122.729158145035 12 344.8 22.4729375331551 616.41203223661 50.7150302302343 -322.327062466845 13 -217 387.164590199142 -778.041359521869 -43.1232306772724 604.164590199142 14 406.7 453.964825235055 501.216043944357 -141.780869179411 47.2648252350546 15 228.6 570.297337604699 127.341170076851 -240.438507681550 341.697337604699 16 -580.1 -710.74364592168 -115.428436604596 -334.027917473724 -130.643645921679 17 -1550.4 -1908.88530439424 -764.297368339865 -427.617327265899 -358.485304394237 18 -1447.5 -1769.87444590603 -603.450748169431 -521.674805924539 -322.374445906029 19 -40.1 259.911132841488 275.621151741692 -615.73228458318 300.011132841488 20 -1033.5 -1487.33448559823 126.498567905612 -706.164082307377 -453.834485598234 21 -925.6 -998.455867620977 -56.148252347449 -796.595880031574 -72.8558676209766 22 -347.8 9.28291863559872 146.059762237946 -850.942680873544 357.082918635599 23 -447.7 -514.32806900171 524.217550717224 -905.289481715514 -66.6280690017102 24 -102.6 90.6468282112164 616.41203223661 -912.258860447827 193.246828211216 25 -2062.2 -2427.13040129799 -778.041359521869 -919.22823918014 -364.93040129799 26 -929.7 -1472.30026168291 501.216043944357 -888.315782261451 -542.600261682906 27 -720.7 -711.337844734089 127.341170076851 -857.403325342762 9.3621552659115 28 -1541.8 -2169.37082611799 -115.428436604596 -798.800737277409 -627.570826117995 29 -1432.3 -1360.10448244808 -764.297368339865 -740.198149212056 72.1955175519208 30 -1216.2 -1164.66710665425 -603.450748169431 -664.282145176323 51.532893345754 31 -212.8 -112.855010601102 275.621151741692 -588.36614114059 99.9449893988981 32 -378.2 -366.205509072795 126.498567905612 -516.693058832816 11.9944909272046 33 76.9 654.968228872491 -56.148252347449 -445.019976525042 578.068228872491 34 -101.3 45.0169196655904 146.059762237946 -393.676681903536 146.316919665590 35 220.4 258.915836564805 524.217550717224 -342.333387282030 38.5158365648053 36 495.6 693.260113935912 616.41203223661 -318.472146172523 197.660113935912 37 -1035.2 -997.747735415115 -778.041359521869 -294.610905063016 37.4522645848846 38 61.8 -78.6191091696023 501.216043944357 -298.996934774755 -140.419109169602 39 -734.8 -1293.55820559036 127.341170076851 -303.382964486494 -558.758205590357 40 -6.9 420.506694757021 -115.428436604596 -318.878258152425 427.406694757021 41 -1061.1 -1023.52907984178 -764.297368339865 -334.373551818356 37.5709201582212 42 -854.6 -802.76639643618 -603.450748169431 -302.982855394389 51.8336035638204 43 -186.5 -377.028992771270 275.621151741692 -271.592158970423 -190.528992771270 44 244 587.020774497149 126.498567905612 -225.519342402761 343.020774497149 45 -992.6 -1749.60522181745 -56.148252347449 -179.446525835098 -757.005221817453 46 -335.2 -683.776999818398 146.059762237946 -132.682762419548 -348.576999818398 47 316.8 195.301448286772 524.217550717224 -85.9189990039966 -121.498551713228 48 477.6 375.06887667921 616.41203223661 -36.2809089158208 -102.53112332079 49 -572.1 -379.515821650486 -778.041359521869 13.3571811723551 192.584178349514 50 1115.2 1661.64513349443 501.216043944357 67.538822561212 546.445133494431

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Dec/09/t1291926992qpwq3icowgul4bo/1lzm91291927104.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/09/t1291926992qpwq3icowgul4bo/1lzm91291927104.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/09/t1291926992qpwq3icowgul4bo/2lzm91291927104.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/09/t1291926992qpwq3icowgul4bo/2lzm91291927104.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/09/t1291926992qpwq3icowgul4bo/3w8mu1291927104.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/09/t1291926992qpwq3icowgul4bo/3w8mu1291927104.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/09/t1291926992qpwq3icowgul4bo/4w8mu1291927104.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/09/t1291926992qpwq3icowgul4bo/4w8mu1291927104.ps (open in new window)

Parameters (Session):

par1 = 12 ; par2 = periodic ; par3 = 0 ; par5 = 1 ; par7 = 1 ; par8 = FALSE ;

Parameters (R input):

par1 = 12 ; par2 = periodic ; par3 = 0 ; par5 = 1 ; par7 = 1 ; par8 = FALSE ;

R code (references can be found in the software module):

par1 <- as.numeric(par1) #seasonal period if (par2 != 'periodic') par2 <- as.numeric(par2) #s.window par3 <- as.numeric(par3) #s.degree if (par4 == '') par4 <- NULL else par4 <- as.numeric(par4)#t.window par5 <- as.numeric(par5)#t.degree if (par6 != '') par6 <- as.numeric(par6)#l.window par7 <- as.numeric(par7)#l.degree if (par8 == 'FALSE') par8 <- FALSE else par9 <- TRUE #robust nx <- length(x) x <- ts(x,frequency=par1) if (par6 != '') { m <- stl(x,s.window=par2, s.degree=par3, t.window=par4, t.degre=par5, l.window=par6, l.degree=par7, robust=par8) } else { m <- stl(x,s.window=par2, s.degree=par3, t.window=par4, t.degre=par5, l.degree=par7, robust=par8) } m$time.series m$win m$deg m$jump m$inner m$outer bitmap(file='test1.png') plot(m,main=main) dev.off() mylagmax <- nx/2 bitmap(file='test2.png') op <- par(mfrow = c(2,2)) acf(as.numeric(x),lag.max = mylagmax,main='Observed') acf(as.numeric(m$time.series[,'trend']),na.action=na.pass,lag.max = mylagmax,main='Trend') acf(as.numeric(m$time.series[,'seasonal']),na.action=na.pass,lag.max = mylagmax,main='Seasonal') acf(as.numeric(m$time.series[,'remainder']),na.action=na.pass,lag.max = mylagmax,main='Remainder') par(op) dev.off() bitmap(file='test3.png') op <- par(mfrow = c(2,2)) spectrum(as.numeric(x),main='Observed') spectrum(as.numeric(m$time.series[!is.na(m$time.series[,'trend']),'trend']),main='Trend') spectrum(as.numeric(m$time.series[!is.na(m$time.series[,'seasonal']),'seasonal']),main='Seasonal') spectrum(as.numeric(m$time.series[!is.na(m$time.series[,'remainder']),'remainder']),main='Remainder') par(op) dev.off() bitmap(file='test4.png') op <- par(mfrow = c(2,2)) cpgram(as.numeric(x),main='Observed') cpgram(as.numeric(m$time.series[!is.na(m$time.series[,'trend']),'trend']),main='Trend') cpgram(as.numeric(m$time.series[!is.na(m$time.series[,'seasonal']),'seasonal']),main='Seasonal') cpgram(as.numeric(m$time.series[!is.na(m$time.series[,'remainder']),'remainder']),main='Remainder') par(op) dev.off() load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Seasonal Decomposition by Loess - Parameters',4,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Component',header=TRUE) a<-table.element(a,'Window',header=TRUE) a<-table.element(a,'Degree',header=TRUE) a<-table.element(a,'Jump',header=TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Seasonal',header=TRUE) a<-table.element(a,m$win['s']) a<-table.element(a,m$deg['s']) a<-table.element(a,m$jump['s']) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Trend',header=TRUE) a<-table.element(a,m$win['t']) a<-table.element(a,m$deg['t']) a<-table.element(a,m$jump['t']) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Low-pass',header=TRUE) a<-table.element(a,m$win['l']) a<-table.element(a,m$deg['l']) a<-table.element(a,m$jump['l']) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable.tab') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Seasonal Decomposition by Loess - Time Series Components',6,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'t',header=TRUE) a<-table.element(a,'Observed',header=TRUE) a<-table.element(a,'Fitted',header=TRUE) a<-table.element(a,'Seasonal',header=TRUE) a<-table.element(a,'Trend',header=TRUE) a<-table.element(a,'Remainder',header=TRUE) a<-table.row.end(a) for (i in 1:nx) { a<-table.row.start(a) a<-table.element(a,i,header=TRUE) a<-table.element(a,x[i]) a<-table.element(a,x[i]+m$time.series[i,'remainder']) a<-table.element(a,m$time.series[i,'seasonal']) a<-table.element(a,m$time.series[i,'trend']) a<-table.element(a,m$time.series[i,'remainder']) a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable1.tab')

Copyright

This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 License.

Software written by Ed van Stee & Patrick Wessa

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